Hierarchical grid transformation for image warping in the analysis of two-dimensional electrophoresis gels

Abstract

Two-dimensional electrophoresis is a widely used method for separating a large number of proteins from complex protein mixtures and for revealing differential patterns of protein expressions. In the computer-assisted proteome research, the comparison of protein separation profiles involves several heuristic steps, ranging from protein spot detection to matching of unknown spots. An important prerequisite for efficient protein spot matching is the image warping step, where the geometric relationship between the gel profiles is modeled on the basis of a given set of known corresponding spots, so-called landmarks, and the locations of unknown spots are predicted using the optimized model. Traditionally, polynomial functions together with least squares optimization has been used, even though this approach is known to be incapable of modeling all the complex distortions inherent in electrophoretic data. To satisfy the need of more flexible gel distortion correction, a hierarchical grid transformation method with stochastic optimization is presented. The method provides an adaptive multiresolution model between the gels, and good correction performance in the practical cross-validation tests suggests that automatic warping of gel images could be based on this approach. We believe that the proposed model also has significance in the ultimate comparison of corresponding protein spots since the matching process should benefit from the closeness of the true spot pairs.

Elastic Registration of Biological Images Using Vector-Spline Regularization

“…3) Landmark Usefulness: Most of the works in electrophoresis image registration is based on landmark matching or spot matching [7], [11], [46]- [49]. On one hand, matching spots is a more complex problem than matching landmarks since their correspondence is unknown and since the number of spots in both images may differ.…”

Elastic Image Registration with Applications to Proteomics

“…Most of the works in electrophoresis image registration is based on spot matching [15,16,17,18,19,20]. On one hand, matching spots is a more complex problem than matching landmarks since their correspondence is unknown and since the number of spots in both images may differ.…”

Protein image alignment via tensor product cubic splines

“…Unfortunately, these distortions cannot be avoided. Even under strictly-controlled laboratory conditions, repeated analysis of the same sample may produce non-identical gels [21,24]. In order to analyze variations in the protein gels obtained from different groups that account for biological variations attributable, for example, to a treatment we must first eliminate distortions to properly align images.…”

“…This technique is also known as image warping [7,10,21], or image registration [8,9,22,23]. The transformed images should have no (or very little) geometrical variations, so that only statistical and biological variation are observed.…”